The approaches described in this section could be pursued, but are not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Numerous techniques, products, and supporting tools have been developed for monitoring and managing the behavior of network devices and networks as a whole. In general, existing management products provide separate network fault, configuration, accounting, performance, and security (“FCAPS”) management functions. Most products that are designed to receive, process and drive distributed information on performance or accounting data, such as products available from Agilent, Narus, XACCT, Cisco, Concord, and Infovista, use a hard-coded software structure, and cannot operate with a mixture of native and non-native processing algorithms. Moreover, these systems are not equipped with features to self-administrate both their structure and their operational functions. Their interfaces are purely devoted to input and output of monitored data; they have no capability for dynamically importing policies to control the collection and the processing of state information on the network devices.
Thus, there is a need for adaptable tools that are capable of optimizing both the collection and processing of behavioral information on the network. There is a need for products that can flexibly accept new features for both input and output functions, and that permit integration of new software elements into their structure and new functions into their behavior, as business needs evolve.
Good network management often requires concurrent consideration of network accounting information and network performance information. However, the separation of accounting and performance data collection in most systems means that managers have difficulty in synchronizing the information provided by distinct tools dealing with performance and accounting.
Moreover, there is a need to dynamically verify the compatibility between different types of network data collectors or between policy sets that drive business-oriented settings. Therefore, there is a need of to have self-manageable tools for processing accounting and performance data on networks. There is also a need for network management data collection systems with the possibility to dynamically tune their monitoring behavior and monitor their structure.
Still another drawback of existing network management data collection systems is that they provide relatively simple data processing, typically limited to aggregation functions, and processing of partial or incomplete data is not considered. This becomes a serious limitation on performing pre-emptive diagnosis, in which only partial data is available. While the polling mechanisms of systems from Agilent, Concord and Infovista are programmable, they are not self-adaptable. As a result, external decisions are needed to modify or tune the settings of the polling mechanisms. There is no intelligence embedded into the processes handling those collectors, and therefore no optimization is performed in collection of data.
The existing tools also do not dynamically provide policies to reschedule all collection and processing features, while checking and validating consistencies between the active collectors and conflict free policy blades driving the operational functions and self-administrative functions. An example of a self-administrative function is dynamically verifying that no conflicting policies are simultaneously active.
Based on the foregoing, there is a clear need for improved ways to simultaneously manage network performance and accounting information.